Beetle antennae search without parameter tuning (BAS-WPT) for multi-objective optimization

Jiang, Xiangyuan; Li, Shuai

doi:10.2298/fil2015113j

Cited by 39 publications

(22 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(2) Beetle antennae search algorithm The beetle antennae search algorithm (BAS) [19], [20] is an intelligent algorithm for searching for an optimal solution. The creation of this algorithm's principle was inspired by how beetles find their food.…”

Section: Swarm Intelligence Algorithmmentioning

confidence: 99%

Global Optimization Algorithm for Cloud Service Composition

Yang

Xue

Liu

et al. 2021

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

Service composition optimization is a classic NP-hard problem. How to quickly select high-quality services that meet user needs from a large number of candidate services is a hot topic in cloud service composition research. An efficient second-order beetle swarm optimization is proposed with a global search ability to solve the problem of cloud service composition optimization in this study. First, the beetle antennae search algorithm is introduced into the modified particle swarm optimization algorithm, initialize the population bying using a chaotic sequence, and the modified nonlinear dynamic trigonometric learning factors are adopted to control the expanding capacity of particles and global convergence capability. Second, modified secondary oscillation factors are incorporated, increasing the search precision of the algorithm and global searching ability. An adaptive step adjustment is utilized to improve the stability of the algorithm. Experimental results founded on a real data set indicated that the proposed global optimization algorithm can solve web service composition optimization problems in a cloud environment. It exhibits excellent global searching ability, has comparatively fast convergence speed, favorable stability, and requires less time cost.

show abstract

Section: Swarm Intelligence Algorithmmentioning

confidence: 99%

Global Optimization Algorithm for Cloud Service Composition

Yang

Xue

Liu

et al. 2021

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

show abstract

“…2. In this paper, the Beetle Antennae Search algorithm [17,18] is used to optimize the current values of the four types of six-coils structures and Maxwell coils as shown in Fig. 2.…”

Section: Simulation Study Of Magnetic Field Gradientmentioning

confidence: 99%

Simulation Research on Forward Problem of Magnetoacoustic Concentration Tomograghy of Magnetic Nanoparticles With Magnetic Induction Based on Multi-Coils

Yan¹,

Gao²,

Cai³

et al. 2021

PIER M

View full text Add to dashboard Cite

Magnetoacoustic concentration tomograghy of magnetic nanoparticles (MNPs) with magnetic induction (MACT-MI) is a multi-physics field imaging method based on the coupling effect of magnetic field and acoustic field. In order to generate a gradient magnetic field with higher uniformity by using lower current excitation, this paper takes the magnetic field gradient of 0.3 T/m as the design objective and utilizes the Beetle Antennae Search Algorithm to optimize the parameters of the excitation current of multiple coils. The uniformity of gradient magnetic field generated by four typical six-coils structures with different radii and distances was compared with that generated by the Maxwell coil, and then the optimal structure of six-coils was determined. By using the finite element method, the physical process of MACT-MI was numerically solved according to the optimization results, and we obtained the one-dimensional and two-dimensional distribution images of magnetic force and sound pressure. The results show that compared with the Maxwell coil, the multi-coil structure can effectively reduce the current excitation and provide a higher uniform gradient magnetic field, which makes the magnetic force of MNPs more uniform and promotes the complete reconstruction of the sound source. These research results can provide research ideas for the optimization of MACT-MI system and lay a foundation for subsequent experiments and even clinical practice.

show abstract

“…Beetle antennae search algorithm (BAS) is a newly proposed metaheuristic algorithm inspired by the searching behavior of longhorn beetles [25,26]. It imitates the function of antennae and the random walk mechanism of beetles in nature, and then two main steps of detecting and searching are implemented.…”

Section: Optimization Algorithm: Beetle Antennae Search Algorithmmentioning

confidence: 99%

“…With only one group of initial parameter, two main steps of detecting and searching are implemented. This algorithm has been applied to different constraint optimization problems extensively and successfully, and the results show fast convergence velocity to global optimum [26].…”

Section: Introductionmentioning

confidence: 99%

Path and function synthesis of multi-bar mechanisms using beetle antennae search algorithm

Zhao

et al. 2020

Filomat

View full text Add to dashboard Cite

Beetle antennae search algorithm (BAS) is based on the searching behavior of longhorn beetles. This newly proposed metaheuristic algorithm is used in the path and function synthesis of multi-bar mechanism. The optimization results are compared with that of other metaheuristic algorithms like genetic algorithm (GA), particle swarm optimization (PSO) and differential evolution (DE) et al. While BAS uses only one group of initial parameters to search the best result, the convergence and efficiency are tested with eight case studies results. Newly added parameter q increases the possibility to find better results during iterations and deals with a higher number of independent parameters efficiently. Revised BAS exhibits good performance both in path synthesis of four-bar mechanism with or without prescribed timing, while optimized parameters increases from 6 to 34, and extends to path and function combined synthesis of Stephenson III six-bar double dwell mechanism with 14 parameters.

show abstract

Beetle antennae search without parameter tuning (BAS-WPT) for multi-objective optimization

Cited by 39 publications

References 5 publications

Global Optimization Algorithm for Cloud Service Composition

Global Optimization Algorithm for Cloud Service Composition

Simulation Research on Forward Problem of Magnetoacoustic Concentration Tomograghy of Magnetic Nanoparticles With Magnetic Induction Based on Multi-Coils

Path and function synthesis of multi-bar mechanisms using beetle antennae search algorithm

Contact Info

Product

Resources

About